在Pandas DataFrame中的if-then-else块中评估多个条件 [英] Evaluating multiple conditions in if-then-else block in a Pandas DataFrame

问题描述

我想通过评估if-then-else块中的多个条件在Pandas DataFrame中创建一个新列。

I want to create a new column in a Pandas DataFrame by evaluating multiple conditions in an if-then-else block.

if events.hour <= 6:
    events['time_slice'] = 'night'
elif events.hour <= 12:
    events['time_slice'] = 'morning'
elif events.hour <= 18:
    events['time_slice'] = 'afternoon'
elif events.hour <= 23:
    events['time_slice'] = 'evening'

运行此命令时，出现以下错误：

When I run this, I get the error below:

ValueError：系列的真值不明确。使用a.empty，a.bool（），a.item（），a.any（）或a.all（）。

ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

因此，我尝试通过添加如下所示的任何语句来解决此问题：

So I tried to solve this by adding the any statement like shown below:

if (events.hour <= 6).any():
    events['time_slice'] = 'night'
elif (events.hour <= 12).any():
    events['time_slice'] = 'morning'
elif (events.hour <= 18).any():
    events['time_slice'] = 'afternoon'
elif (events.hour <= 23).any():
    events['time_slice'] = 'evening'

现在不会出现任何错误，但是当我检查time_slice的唯一值时，它仅显示'night'

Now I do not get any error, but when I check the unique values of time_slice, it only shows 'night'

np.unique(events.time_slice)

array（['night']，dtype =对象）

array(['night'], dtype=object)

我该如何解决这个问题，因为我的数据中包含的样本应该会出现上午，下午或晚上 。谢谢！

How can I solve this, because my data contains samples that should get 'morning', 'afternoon' or 'evening'. Thanks!

推荐答案

您可以使用 pd.cut（）方法，以便对数据进行分类：

you can use pd.cut() method in order to categorize your data:

演示：

In [66]: events = pd.DataFrame(np.random.randint(0, 23, 10), columns=['hour'])

In [67]: events
Out[67]:
   hour
0     5
1    17
2    12
3     2
4    20
5    22
6    20
7    11
8    14
9     8

In [71]: events['time_slice'] = pd.cut(events.hour, bins=[-1, 6, 12, 18, 23], labels=['night','morning','afternoon','evening'])

In [72]: events
Out[72]:
   hour time_slice
0     5      night
1    17  afternoon
2    12    morning
3     2      night
4    20    evening
5    22    evening
6    20    evening
7    11    morning
8    14  afternoon
9     8    morning

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